Spring 2017 Class Materials
All materials listed here are licensed for reuse under Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
Lecture Notes
by Elizabeth Purdom and Adityanand Guntuboyina
# | Title | Chapter (pdf) | Code (html) | Code(Rmd) |
---|---|---|---|---|
01 | Review of probability | html | Rmd | |
02 | Comparing Groups and Hypothesis Testing | html | Rmd | |
03 | Fitting curves to data | html | Rmd | |
04 | Visualizing Multivariate Data | html | Rmd | |
05 | Multiple Regression | html | Rmd | |
06 | Logistic Regression | html | Rmd | |
07 | Regression and Classification Trees | html | Rmd |
Labs
by Boying Gong
# | Title | Jupyter Link |
---|---|---|
01 | Intro to R | link |
02 | Intro to RStudio | link |
03 | Density curves, violin plots | link |
04 | Permutation tests, t-tests, Bonferonni correction | link |
05 | Bootstrap and parametric Confidence Intervals, Linear regression | link |
06 | Linear models, plotting, polynomial models | link |
07 | Loess and Pairs plots | link |
08 | Heatmaps, PCA, brief intro to ggplot | link |
09 | More PCA | link |
10 | Multiple linear regression models | link |
11 | Prediction with linear regression | link |
12 | Regression diagnostics and logistic regression | link |
13 | Regression and classification trees | link |